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Lecture 22 Deployment Strategies Fixed Platforms Collin Roesler 18 July 2007.

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Presentation on theme: "Lecture 22 Deployment Strategies Fixed Platforms Collin Roesler 18 July 2007."— Presentation transcript:

1 Lecture 22 Deployment Strategies Fixed Platforms Collin Roesler 18 July 2007

2 Issues related to fixed platform observatories, examples from the Gulf of Maine Ocean Observing System Moored array issues System Integration Instrument characterization/calibration Biofouling Data Analysis

3 Moored Arrays Motivation Space/time (x, y, z, t) sampling strategies Advantages –highly resolved time scales –real time telemetry (line of site wireless, cell phone, satellite, irridium) –6 month deployments (TOGA TAO 12 months) Disadvantages –no spatial information without other data sources (modeling, remote sensing, mobile platforms, shipboard surveys) –biofouling

4 Time and Space Scales

5 Moored Arrays Motivation Space/time (x, y, z, t) sampling strategies Advantages –highly resolved time scales –real time telemetry (line of site wireless, cell phone, satellite, irridium) –6 month deployments (TOGA TAO 12 months) Disadvantages –no spatial information without other data sources/arrays (modeling, remote sensing, mobile platforms, shipboard surveys, arrays) –biofouling

6 System Integration Mooring types –subsurface float vs. surface expression –taut vs. elastic vs. scoping

7 System Integration Mooring types –subsurface float vs. surface expression –taut vs. elastic vs. scoping System control –centralized control (wired vs. inductive modem) –centralized vs. local data storage Power –centralized power vs. local power –solar cells, traditional batteries, on board generation Real estate –everyone wants the surface positions –flow and drag simulations Data telemetry –band width limitations –onboard processing –redundant telemetry

8 Calibrations Instrument characterization/calibration pure water cals total offset biofouling instrument drift time cal value - Post-recovery post-clean calibration (3) biofouling = (3) – (2) drift = (3) – (1) - Re-deployment calibration (4) - Pre-deployment calibration (1) - Post-recovery pre-clean calibration (2) Total offset = (2) – (1)

9 Calibrations Instrument characterization/calibration pure water cals total offset biofouling instrument drift time In situ value - Validation (new deploy – corrected) - Linear trend - Step function trend

10 Instrument characterization/calibration Calibrations Environmental characterization –temperature –salinity –pressure –irradiance

11 Chlorophyll Fluorometer Characterization

12 Chlorophyll Fluorometer Characterization Temperature Dependence Slope is the warmup effect Deployment Temperature Effect

13 Range 1 to 5 counts/ o C Chlorophyll Fluorometer Characterization Temperature Dependence The temperature dependence, of course, varies between sensors and between sensor type

14 Chlorophyll Fluorometer Characterization Correction for Temperature Dependence ~0.25  g/l Compounding Issue: The biggest temperature effect occurs in the winter (  T), and that is when chlorophyll is lowest.

15 Biofouling

16 Prevention –toxic coatings –copper shutters –copper tape –copper tubing

17 Biofouling Identification –Long term trends

18 Biofouling Identification –Long term trends –Redundancy

19 Biofouling Identification –Long term trends –Redundancy

20 Biofouling Identification –Long term trends –Redundancy –Temporal patterns

21 Biofouling Correction –after the fact: calibrations –real time redundancy signal separation flagging

22 Biofouling Correction –after the fact: calibrations a(676) corrected F chl (mg/m 3 ) / 0.0145 (m 2 /mg)

23 Biofouling Correction –after the fact: calibrations –real time Redundancy (is signal real?) Signal separation (is it one component?) Flagging (pretty sure it is an artifact)

24 Calibrated Chlorophyll Fluorescence Time Series A B E I


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